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Abstract:

A method is provided for providing a 3D image data record relating to a
biological object with suppressed aliasing artifacts overlapping the
field of view caused by an incomplete geometric capture of the object by
a computed tomography. A first 3D image data record is provided to
describe a subarea of the object. A second 3D image data record is
obtained by the computed tomography including data relating to the
subarea of the object and is registered with the first 3D image data
record. Data of the second 3D image data record is extended and/or
amended according to data of the first 3D image data record. A part of
such data of the second 3D image data record can be assigned to an
aliasing artifact overlapping the field of view and thus generates a
modified second 3D image data record with suppressed aliasing artifacts
overlapping the field of view.

Claims:

1. A method for providing a 3D image data record of a biological object
with a suppressed aliasing artifact overlapping a field of view, wherein
an aliasing artifact overlapping the field of view is caused by an
incomplete geometric capture of the biological object by a computed
tomograph, comprising: providing a first 3D image data record describing
a subarea of the biological object; obtaining a second 3D image data
record of the biological object by the computed tomograph, wherein the
second 3D image data record includes data relating to the subarea of the
biological object described by the first 3D image data record;
registering the first 3D image data record with the second 3D image data
record; extending and/or amending data of the second 3D image data record
as a function of data of the first 3D image data record so that a part of
the data of the second 3D image data record can be assigned to the
aliasing artifact overlapping the field of view; and generating a
modified second 3D image data record with the suppressed aliasing
artifact overlapping the field of view.

2. The method as claimed in claim 1, further comprising: obtaining a 2D
image data record from the modified second 3D image data record, and
generating a forward projection image and/or an x-ray sectional image
from the 2D image data record.

3. The method as claimed in claim 1, wherein the first 3D image data
record is registered with the second 3D image data record by:
positionally and dimensionally assigning the data of the first 3D image
data record to the data of the second 3D image data record; determining a
degree of match between the data assigned to one another; and modifying
the data of the first 3D image data record assigned to the data of the
second 3D image data record by draw points so that the degree of match
increases.

4. The method as claimed in claim 1, wherein the first 3D image data
record is provided by: providing at least two image data records relating
to at least two comparison objects which are similar or identical to the
biological object; and determining the first 3D image data record
describing the subarea of the biological object by obtaining an averaged
effective image data record from the at least two image data records.

5. The method as claimed in claim 4, wherein the at least two image data
records of the at least two comparison objects are created by computed
tomography images, and wherein the computed tomography images are
segmented.

6. The method as claimed in claim 1, wherein the first 3D image data
record is stored in a database, and wherein the database comprises at
least two different 3D image data records describing different subareas
of the biological object or different biological objects.

7. The method as claimed in claim 1, wherein a first data is selected in
the first 3D image data record by a binary segmentation and is assigned
to a specific type of biological tissue of the biological object, wherein
a second data is selected in the second 3D image data record by a binary
segmentation and is assigned to a same type of the biological tissue of
the biological object, and wherein the first 3D image data record is
registered with the second 3D image data record according to the first
and the second data.

8. A computed tomography, comprising: an x-ray source; an x-ray detector;
and an image evaluation apparatus adapted to execute a method comprising
the steps of: providing a first 3D image data record describing a subarea
of the biological object; obtaining a second 3D image data record of the
biological object by the computed tomograph, wherein the second 3D image
data record includes data relating to the subarea of the biological
object described by the first 3D image data record; registering the first
3D image data record with the second 3D image data record; extending
and/or amending data of the second 3D image data record as a function of
data of the first 3D image data record so that a part of the data of the
second 3D image data record can be assigned to the aliasing artifact
overlapping the field of view; and generating a modified second 3D image
data record with the suppressed aliasing artifact overlapping the field
of view.

9. The computed tomograph as claimed in claim 8, wherein the x-ray
detector is a flat panel detector.

Description:

CROSS REFERENCE TO RELATED APPLICATION

[0001] This application claims priority of German application No. 10 2011
075 917.4 filed May 16, 2011, which is incorporated by reference herein
in its entirety.

FIELD OF INVENTION

[0002] The invention relates to a method for providing a 3D image data
record relating to a biological object with suppressed aliasing artifacts
overlapping the field of view, which are caused by an incomplete
geometric capture of the biological object by means of a computed
tomograph. The invention also relates to a computed tomograph having an
x-ray source, a detector and an image evaluation apparatus, which is
embodied to execute such a method.

BACKGROUND OF INVENTION

[0003] The x-ray and/or tomography images obtained by x-ray image
recording apparatuses, in particular computed tomographs, may comprise
various image artifacts. One type of image artifact is used such that the
measured object is not completely captured during the measuring process
in terms of its geometric extension. Part of the object under measurement
is positioned outside of the field of view and is in this manner
truncated, so to speak, in respect of the image obtained therefrom. The
image artifacts resulting herefrom can be referred to below as aliasing
artifacts overlapping the field of view. They play an essential role
particularly in computed tomographs, since a three-dimensional image
obtained by means of back projection is frequently based on a plurality
of projection images, not all of which capture the object to be measured
wholly or completely. The object is not constantly completely within the
field of view, namely during the measuring process.

[0004] This unwanted data shortening may be meaningful in the case of all
computed tomographical scan apparatuses, but nevertheless plays a
significant roll particularly with flat panel computed tomographs (see
"W. A. Kalender and Y. Kyriaku. Flat-detector CT. Eur Radiol.
(11):2767-79, 2007"). With flat panel detector computed tomographs, the
view field and/or field of view of the detector which can be captured
during the measurement only amounts to approximately 20-25 cm in terms of
diameter. This restriction makes the prevention of aliasing artifacts
overlapping the field of view almost impossible. Aliasing artifacts
overlapping the field of view significantly impair the quality of a
resulting x-ray and/or tomography image. The artifacts not only herewith
appear in the vicinity of the image edge, but instead also influence
central areas of the recorded image.

[0005] Aliasing artifacts overlapping the field of view would then not
occur for instance if the x-ray radiation was not attenuated at all
border areas of the field of view. A defined transition in respect of the
absorption values to zero then results. If this transition is however not
correctly given, this results during the computed tomography recordings
particularly after filtered back projection (see for instance "A. C. Kak
and M. Slaney. Principles of Computerized Tomographic Imaging. IEEE
Press, 1988", "L. A. Feldkamp, L. C. Davis, and J. W. Kress. Practical
cone-beam algorithm. J. Opt. Soc. Am. A, 1(6):612-619, 1984") in the
effect that aliasing artifacts overlapping the field of view appear and
an apparent increase in the x-ray radiation attenuation values to the
image borders is observed. A pale white ring appears in the computed
tomography image beyond the border of the field of view. Strip-like
artifacts also result outside of the actual field of view area.

[0006] Aliasing artifacts overlapping the field of view are generally
suppressed such that image areas at the edge of the field of view, to
which attenuation values greater than zero are assigned, are extrapolated
such that a smoothed value curve is produced toward the x-ray absorption
value zero. According to a known method, the truncation areas are
extrapolated in the computed tomography projection images used for the
back projection onto an attenuation value of zero and it is only then
that the filtered back projection is implemented. Within the scope of
this extrapolation method, objects are approached for instance by means
of a water cylinder (see "Hsieh J, Chao E, Thibault J, Grekowicz B, Horst
A, McOlash S and Myers T J, 2004, A novel reconstruction algorithm to
extend the CT scan field-of-view Med. Phys. 31, 2385-91"). The patient as
a whole can also be approximated as a water ellipsoid, so that in this
manner data exists for the extrapolation (see "Maltz J S, Bose S, Shukla
H P and Bani-Hashemi A R, 2007, CT truncation artifact removal using
water-equivalent thicknesses derived from truncated projection data Proc.
IEEE Eng. Med. Biol., Soc. 2007. 2907-11"). A square extrapolation is for
instance known from "Sourbelle K, KachelrieB M and Kalender W A, 2005,
Reconstruction from truncated projections in CT using adaptive
detruncation Eur. Radiol. 15, 1008-14", while a so-called sinogram
interpolation is described in "Zamyatin A A and Nakanishi S, 2007,
Extension of the reconstruction field of view and truncation correction
using sinogram decomposition Med. Phys. 34, 1593-604". Further
extrapolation methods are known from the following publications: "Janoop
K P and Rajgopal K, 2007, Estimation of missing data using windowed
linear prediction in laterally truncated projections in cone-beam CT
Proc. IEEE Eng. Med. Biol. Soc. 2007, 2903-6", "Starman J, Pelc N, Strobe
N and Fahrig R, 2005, Estimating 0th and 1st moments in C-arm
CT data for extrapolating truncated projections Proc. SPIE 5747, 378-87"
and "Sourbelle K, KachelrieB M and Kalender W A, 2005, Reconstruction
from truncated projections in CT using adaptive detruncation Eur. Radiol.
15, 1008-14".

[0007] The methods known from the prior art have the objective of
improving the image quality within the field of view area, but
nevertheless impairing an image modification or quality improvement
outside of the field of view area. In the event that several border areas
are truncated in the computed tomography projection images, further
serious disadvantages result. With the majority of methods, at least one
non-truncated projection image is needed in order to ensure the
fulfillment of a consistency criterion. A conversion from 3D into 2D data
is frequently extremely time-consuming. Extremely shortened data records,
such as are the rule with flat panel computed tomographs, cannot be
overcome by the usual methods with respect to the aliasing artifacts
overlapping the field of view. In addition, anatomical information is
frequently lost. The contour of a patient is generally not correctly
reproduced, which hampers a treating physician during an operation for
instance, when navigating instruments in the body of the patient with the
aid of the computed tomography image.

SUMMARY OF INVENTION

[0008] It is the object of the invention to provide a method and an x-ray
image recording apparatus with which aliasing artifacts overlapping the
field of view can still be better suppressed.

[0009] This object is achieved by a method and a computed tomography which
comprise the features of the claims.

[0010] The inventive method is used to provide a 3D data record relating
to a biological object with suppressed aliasing artifacts overlapping the
field of view, which are caused by an incomplete geometric detection of
the biological object by means of a computed tomograph. It includes the
following steps: [0011] a) providing at least one first 3D image data
record to describe at least one subarea of the biological object; [0012]
b) obtaining a second 3D image data record with respect to the biological
object by means of a computed tomograph, [0013] wherein the second 3D
image data record includes data relating to the at least one subarea of
the biological object described by the first 3D image data record;
[0014] c) registering the first 3D image data record with the second 3D
image data record; [0015] d) extending and/or amending the second 3D
image data record as a function of data of the first 3D image data record
for at least one part of such data of the second 3D image data record,
which can be assigned to an aliasing artifact overlapping the field of
view and thus generating a modified second 3D image data record with
suppressed aliasing artifacts overlapping the field of view.

[0016] If the second 3D image data record obtained on the biological
object is to be incomplete with respect to the geometric capture of the
biological object, this is in particular a cause of aliasing artifacts
overlapping the field of view occurring in the resulting computed
tomography images. By providing the at least one first 3D image data
record, incomplete data can then in particular be extended in the second
3D image data record such that the aliasing artifacts overlapping the
field of view are suppressed or even completely prevented. By means of
the first 3D image data record, the appearance of aliasing artifacts
overlapping the field of view is already prevented so that if necessary,
a subsequent modification and/or processing of a resulting computed
tomography image can be omitted with respect to the retouching of
aliasing artifacts overlapping the field of view. The method therefore
does not suppress aliasing artifacts overlapping the field of view by
processing the image of a resulting image but instead assesses in
advance, by extending the data structure underlying the image so that the
artifacts do not appear in the first place. The provision of a concrete
first 3D image data record dispenses with imprecise and rough assumptions
for the modification of the second 3D image data record. A qualitatively
improved and modified second 3D image data record is thus available, from
which meaningful computed tomography images can be obtained. Aliasing
artifacts overlapping the field of view are prevented very efficiently.
Assessing the resulting computed tomography images is thus easier for a
person.

[0017] Provision can be made in particular for several 3D image data
records to be obtained for instance by means of the computed tomograph in
order to describe several projection images of the biological object and
then the second 3D image data record is obtained with the aid of these 2D
image data records by means of back projection. In particular, provision
can be made for the first 3D image data record to provide an image model
of the biological object. Registration is in particular understood to
mean the image registration of the first 3D image data record with the
second 3D image data record. This may in particular result in the
assignment of the first and second 3D image data record which is correct
in terms of position and/or form, for instance by way of a suitable
coordinate transformation. The extension and/or amending of the data of
the second 3D image data record can either take place directly by means
of the data of the first 3D image data record or new data can however be
obtained on the basis of the data of the first 3D image data record, with
the aid of which the data of the second 3D image data record is extended
and/or amended. Data of the second 3D image data record, which can be
assigned to an aliasing artifact overlapping the field of view, may in
particular be such data which can be assigned to a border area of the
image, which is described by the 3D image data record.

[0018] The method preferably includes the further step of obtaining a 2D
image data record from the modified second 3D image data record and
herefrom a computed tomography image, in particular a forward projection
image and/or an x-ray sectional image is generated. Forward projection
images and x-ray sectional images allow a meaningful interpretation of
the measuring data by means of an operating person. Since, within the
scope of the method, aliasing artifacts overlapping the field of view in
such 2D images are prevented particularly effectively, a very realistic
image of the actual characteristics of the measuring object is obtained.

[0019] Step c) preferably includes the following sub-steps: [0020] c1)
assigning data of the first 3D image data record to data of the second 3D
image data record in a fashion which is correct in terms of position and
dimension; [0021] c2) determining a comparison value, which is a measure
of the degree of the match between the data assigned to one another in
step c1). The comparison value can be in particular a similarity value in
respect of an image comparison of the image assigned to the first 3D
image data record and of the image assigned to the second 3D image data
record. In order to determine the similarity of two images, methods known
from the prior art can be used; [0022] c3) modifying the data of the
first 3D image data record assigned to the second 3D image data record in
step c1) such that the comparison value changes compared with the
comparison value determined in step c2) such that the degree of matching
increases, particularly by amending the first 3D image data record with
the aid of draw points. Provision can in particular be made for the first
3D image data record to be modified such that it compares at least a
sub-quantity of the second 3D image data record in respect of its image
similarity. This can take place for instance in particular pixel by pixel
or voxel by voxel, wherein the gray-scale value deviation in the two
image data records can be used as a comparison value. Images of an object
with a specific contour can be assigned in particular to the 3D image
data records, wherein this contour can be provided with draw points at
specific points. Provision can then be made for the contour of the image
described by the first 3D image data record preferably to be changeable
in terms of image in the vicinity of the draw points. Draw points may in
particular be understood to mean anchor points in a vector-graphical
representation of the image assigned to the first 3D image data record;
[0023] c4) preferably repeating steps c1) to c3).

[0024] The approximation of the first 3D image data record to the second
3D image data record preferably therefore takes place iteratively. In
this way, deviations in respect of the shape and design of a mirroring
image object in the first 3D image data record can be adjusted such that
the image registration in the second 3D image data record is optimized.
The extension and/or amendment of the second 3D image data record then
take place in an even more realistic fashion.

[0025] The first 3D image data record provided in step a) is preferably
obtained with the following sub-steps: [0026] Providing at least two
image data records relating to at least two comparison objects, which are
embodied in a similar or identical fashion to the object. [0027]
Determining the first 3D data record in order to describe the at least
one subarea of the biological object by obtaining an averaged effective
image data record from the at least two image data records.

[0028] Biological objects of the same type (e.g. hand, hip, etc.) usually
indicate variations from living being to living being. It is therefore
advantageous to provide an averaged image of the biological object in
order to be able to amend or extend the second 3D image data record in a
very universal fashion. Faults in the visual description of the
biological object are kept to a minimum. The first 3D image data record
may then be assigned in particular to a statistical shape model of an
anatomical structure.

[0029] The at least two image data records of the at least two comparison
objects are then preferably created with the aid of computed tomography
images of real comparison objects, wherein a segmentation of the computed
tomography images is implemented in the creation step. Real comparison
objects may in particular be real body parts of living beings, from which
image data is obtained. This image data can then be processed such that
an average image is generated from the individual images which then forms
the basis of the first image data record. A first 3D image data record is
herewith created, which reproduces the real situation very well.
Alternatively, provision can however also be made for the first 3D image
data record to be obtained with the aid of an image simulation method,
e.g. a method of constructive solid body geometry (e.g. CAD). Computed
tomography and/or magnetic resonance data may form the basis of the first
3D image data record.

[0030] A database with at least two different 3D image data records is
preferably provided in step a), which describe different subareas of a
biological object or different biological objects. For instance, the
database may include different 3D image data records relating to
different body parts. The image registration can then take place such
that the most suitable 3D image data record is selected from the 3D image
data records available in the database, i.e. that image data record which
features the greatest similarity to an image object in the second 3D
image data record. Provision can however also be made for the most
suitable 3D image data record to be manually selected for instance by
means of an operating person. It is then ensured that the second 3D image
data record is only extended and/or amended by such data which also
corresponds to the actually existing real situation.

[0031] First data is preferably selected in the at least one first 3D
image data record provided, in particular by way of a binary
segmentation, which can be assigned to a specific biological tissue type
of the biological object and in which obtained second 3D image data
record, second data is selected, in particular by way of a binary
segmentation, which can be assigned to the same biological tissue type.
In step c), the image registration preferably then takes place with the
aid of the first and second data. For instance, provision can be made for
the first and second data to be selected such that it corresponds to bone
material of the biological object if the biological object includes bone
material and soft tissue. Then, in step c), the image registration can be
implemented in two stages, wherein in a first stage, an image
registration takes place with the aid of the first and second data
assigned to the bone material and in a second stage downstream of the
first stage, a refined image registration takes place with the aid of the
data of the first and second image data record, which are assigned to the
soft tissue. A particularly precise and reliable image registration is
ensured in this way, thereby rendering possible a correct extension and
amendment of the data of the second 3D image data record.

[0032] An inventive computed tomograph includes an x-ray source, a
detector and an image evaluation apparatus, which is embodied to execute
the inventive method. The computed tomograph may in particular include an
x-ray C-arm and be embodied as a PET/CT system. Provision can in
particular also be made for the detector to be embodied as a flat panel
detector. The method is then particularly effective for suppressing the
aliasing artifacts overlapping the field of view.

[0033] The preferred embodiments represented with reference to the
inventive method and their advantages apply accordingly to the inventive
computed tomographs.

BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The invention is explained in more detail below with reference to
exemplary embodiments, in which:

[0035]FIG. 1 shows a schematic representation of an x-ray C-arm computed
tomograph; and

[0036]FIG. 2 shows a schematic illustration of an exemplary embodiment of
the inventive method.

DETAILED DESCRIPTION OF INVENTION

[0037] Identical or functionally identical elements are provided with the
same reference characters in the figures.

[0038]FIG. 1 shows a computed tomograph 10 with an x-ray C-arm 18, to one
end of which an x-ray source 12 is fastened which emits x-ray radiation S
in the direction of an x-ray detector 14. A patient 16 is arranged on a
couch between the x-ray source 12 and the x-ray detector 14, wherein a
body part of the patient is irradiated by the x-ray radiation S.

[0039] The x-ray C-arm 18 is embodied to be rotatable and can in this way
detect the body part of the patient 16 from different perspectives or at
different angles. In this way, different x-ray projection images can be
detected by way of the x-ray detector 14, which are transferred by way of
a computer 20. A 3D image data record 28 can be reconstructed from the
projection images by way of a method for back projection. The 3D image
data record 28 of the body part is shown schematically in FIG. 2. In the
exemplary embodiment, the body part is an arm 22 of the patient 16. The
arm 22 is only detected in one subarea 32 and thus incompletely on
account of the restricted view field of the x-ray source 12 and x-ray
detector 14. In the exemplary embodiment, the hand is almost partially
truncated. The capture area S1 does not cover the arm 22 completely. If a
3D image is generated from the 3D image data record 28, e.g. by means of
forward projection, this indicates aliasing artifacts overlapping the
field of view or truncation artifacts on account of the truncated hand.

[0040] A method is therefore proposed, with the aid of which missing
information in the defective 3D image data record 28 can be extended.
Statistical shape models of anatomical structures are used here. Such a
model is formed by a 3D master image 26 of the arm 22. The 3D master
image 26 covers a larger subarea 34 of the arm 22 than the 3D image data
record 28. Such a statistical shape model may be generated on the arm 22
(or on a hip or a shoulder region for instance) such that information
from various recorded and segmented computed tomography data records are
used. Provision is made for the 3D master image 26 to exist in a database
24 in the computer 20. Different computed tomography data records of the
respective anatomical regions may exist here.

[0041] Within the scope of a binary segmentation, bones and soft tissue
material are initially separated from one another. The result of this
segmentation provides data records, which minor surface forms and are
stored in the database. Different methods can be used to generate the
surface, like for instance thin plate splines or surface morphing.

[0042] A similar segmentation to the 3D master image 26 is also
implemented on the 3D image data record 28. Image areas, which can be
assigned to bone material, can in this way similarly be distinguished
from image areas which correspond to the soft tissue.

[0043] A 3D-3D image registration then takes place automatically or
manually between the 3D image data record 28 and the 3D master image 26.
The image areas, which correspond to the bone material, are used here as
a first match criterion for the image registration. An adjustment by
means of the image areas, which correspond to the soft tissue, can take
place in a second step within the scope of a refined image registration.
This image registration takes place in step R.

[0044] Within the scope of this image registration, the 3D master image 26
stored in the database 24 can be adjusted to the subarea 32 in the 3D
image data record 32 within the scope of a deformation method (e.g.
thin-plates spline-warping) such that a good match is achieved.

[0045] A modified 3D image data record is produced, in which the original
area S1 of the 3D image data record 28 is extended to an area S2 on
account of the additional information of the 3D master image 26. The
subarea 32 of the 3D image data record 28 is herewith extended by the
extension area 36, which results from the subarea 34 of the 3D master
image. As a result, the modified 3D image data record 30 is achieved.

[0046] The thus resulting modified 3D image data record 30 can now be
projected forwards so that a projection image results in which the
aliasing artifacts overlapping the field of view are suppressed. The thus
obtained computed tomography image can also be smoothed by way of a
histogram analysis, so that the image quality is improved.

[0047] The presented method is advantageous in that very defective or
noisy x-ray image data can be significantly improved in respect of their
quality by the statistic shape model. The 3D master image 26 provides
anatomically correct data, by means of which a very precise extrapolation
of the 3D image data record 28 is possible. Extrapolation methods known
from the prior art must instead be based here on water ellipsoids for
instance, since no anatomical information exists in the truncation area.
The shape and design of the patient can now be precisely considered.
Additional sensors are not necessary.